@emollick To me that doesn't matter that much. There's a million dumb tasks that I have to do, and a competent open weight model will do a more thorough job. I don't need Einstein to help me shovel shit
I can attest to this recipe from @MiaAI_lab. It's much faster than before.
Got it to help me fix and reconcile three years of QuickBooks in about 4 hours.
They can pry my sparks from my cold dead hands 😂
Stop what you’re doing and look at this: (2) Sparks for open-source, frontier-level AI at home!
No subscriptions. No API rate limits. No hourly caps.
Raw benchmarks are placing this recipe right above the entire landscape—trailing only absolute giant frontier models (fable and gpt 6) and I do not make that statement lightly.
By ditching brute-force hardware scaling and moving to an optimized stack (EXL3 4bpw on 2 nodes vs traditional heavy FP8 on 4 nodes), Mia Labs just proved that clever engineering is the ultimate margin expander:
Prefill: 1,554 tok/s (vs 961 tok/s)
Structured Decode: 67.9 tok/s (more than 2x faster)
Context Pool: 850k to 1.85M tokens
Quality Loss: Essentially zero (0.0245 KLD vs teacher)
This is what monetizing compute actually looks like. Can this even be real? This is the one.. @Zai_org can you start getting @MiaAI_lab early access to models for zero day support on GLM 5.5 and 6? I need to schedule days off..
#thisismysuperbowl #fantasyfootballisoverrated @NVIDIAAI@MiaAI_lab https://t.co/JEipuzueuu
@GPTWare if it's on sparks, qwen is better for responsiveness. glm is exceptionally smart, but it gets really sluggish as context grows. I traded a little quality for much higher productivity by using qwen/next.
I was wondering where the gpu modding scene was...
I love what these guys at GPU Lab are doing, looks like this guy Greg has been at it for years. Very cool!
48GB 4090 water blocks available now from https://t.co/CCxcZigEKU
if you've been holding out because the 2-slot air coolers are loud, you can now use them on your own custom loop's. Video review and install guide here: https://t.co/zQix5slc6j
@MiaAI_lab how would you compare this to glm5.3-flash using your EXL3 2x spark recipe? I don't want to lose the quality from glm, but I need something faster as my orchestrator. glm gets really bogged down >200k context
@jensenloke@Tech2Wild@QwenDevs How's the speed on 2x sparks? How do you rank it on skill/intelligence versus glm5.3-flash, if you've used it? glm5.3-flash is terrific, but on two sparks, it takes forever to get a response, especially when context starts getting long
@alexellisuk The model is really good, but really slow on two Sparks. What I've done is have it shove work to two Qwen 27B subagents on 3090s which are about 4x faster, and keeps the main context shorter for longer.